Fuzzy Fusion for Collision Avoidance
Fuzzy Fusion for Collision Avoidance
- New search for: Rezaei, Mahdi
- New search for: Klette, Reinhard
- New search for: Rezaei, Mahdi
- New search for: Klette, Reinhard
Abstract In this chapter we discuss how to assess the risk level in a given driving scenario based on the eight possible inputs: driver’s direction of attention (yaw, roll, pitch), signs of fatigue or drowsiness (yawning, head nodding, eye closure), and from road situations (distance, and the angle of the detected vehicles to the ego-vehicle). Using a fuzzy-logic inference system, we develop an integrated solution to fuse, to interpret, and to process all of the above information. The ultimate goal is to prevent a traffic accident by fusing all the existing “in-out” data from inside the car cockpit and outside on the road. We aim to warn the driver in case of high-risk driving conditions and to prevent an imminent crash.
Document information
Fuzzy Fusion for Collision Avoidance
2017-01-01
17 pages
Article/Chapter (Book)
Electronic Resource
English
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